Workspace Allocation Control for Building Energy Efficiency
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Solution Overview
Problem
Many buildings, particularly offices and recreational facilities, face inefficiencies in energy consumption due to unused workspaces being heated, cooled, and lit as if occupied, resulting from shifts in usage patterns brought on by hybrid working models and COVID-19-related changes.
Innovation Solution
An energy optimization engine that allocates workspaces based on an energy conservation strategy, automatically adjusts environmental conditions like temperature, humidity, and lighting, and controls electronic equipment to minimize energy usage by identifying active and inactive workspaces and optimizing their settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If workspaces are maintained with optimal environmental conditions (heating, cooling, lighting) to ensure readiness for use, then user comfort and workspace availability are improved, but energy consumption increases significantly when workspaces remain unused
Solution Approach 1:
The system dynamically adjusts environmental conditions based on real-time occupancy detection. When a workspace is detected as occupied, the system maintains optimal temperature, lighting, and HVAC settings. When unoccupied, the system automatically reduces these settings to conserve energy, thus adapting the workspace state according to actual usage needs
Solution Approach 2:
The system implements a feedback loop using occupancy sensors to detect whether workspaces are in use. This feedback information triggers automated responses through control systems that adjust environmental conditions accordingly, ensuring energy is consumed only when necessary for actual workspace utilization
2Productivity
If all workspaces are kept ready with optimal environmental settings, then users can access any workspace immediately, but energy is wasted on unused workspaces
Solution Approach 1:
Instead of uniformly maintaining all workspaces at optimal conditions, the system applies different environmental qualities to different workspaces based on their actual occupancy status. Occupied workspaces receive full environmental support while unoccupied ones are placed in energy-saving modes, creating localized quality adjustments throughout the facility
3Use of energy by moving object
If the system automatically adjusts environmental conditions based on occupancy, then energy efficiency is improved, but system complexity increases due to multiple sensors and control mechanisms
Solution Approach 1:
The system employs multi-functional integrated control units that combine occupancy sensing, environmental monitoring, and HVAC/lighting control capabilities. These universal devices perform multiple functions simultaneously, reducing the overall number of separate components needed while maintaining comprehensive automated control
Data Source
AI summary
Some examples relate to optimizing energy efficiency associated with workspaces in a building. In one specific example, a system can receive a selected time from a user for reserving a workspace in a building, The system can determine a recommended workspace for the user at the selected time based on an energy efficiency strategy. The system can then transmit at least one control signal to at least one control system associated with the recommended workspace. The at least one control system can receive the at least one control signal and responsively adjust at least one environmental condition associated with the recommended workspace from a first setting to a second setting. The at least one control system can adjust the at least one environmental condition from the first setting to the second setting by the selected time or within a predefined timeframe after the selected time.